Audio recording obfuscation

ABSTRACT

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selectively obfuscating audio. One of the methods includes detecting, by a security system for a premises, that a person who was within a threshold area for the premises was likely uttering a sound; determining, using data from one or more sensors, a likelihood that the person was communicating with the security system at the premises; determining whether the likelihood satisfies a threshold likelihood and that the person&#39;s voice should not be obfuscated; and in response to determining whether the likelihood satisfies the threshold likelihood and that the person&#39;s voice should not be obfuscated, selectively obfuscating the person&#39;s voice or maintaining, in memory, an audio signal i) that encodes the person&#39;s voice and ii) was captured by a microphone that was physically located at the premises.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No.63/304,744, filed Jan. 31, 2022, the contents of which are incorporatedby reference herein.

BACKGROUND

The operation of connected devices within a property can be integratedto improve monitoring of the property. For example, data gathered by theconnected devices can be aggregated to determine when people are presentin the property.

SUMMARY

Some premises, e.g., homes or offices, have devices, such as smartdoorbells, that can record audio of the environment surrounding thepremises. This audio can be used to deter theft, communicate with peopleapproaching the premises, or both.

In some instances, the audio can accidently encode data that is notnecessary for a security system, a person at the premises, or both. Forinstance, the audio might encode speech of a home owner talking tothemselves as they approach their home.

To reduce a likelihood that audio not required by the security systemwill be recorded, stored in memory, e.g., in a long term memory,transmitted across a network, or a combination of these, a securitysystem can determine a likelihood that a person was communicating withthe security system. Some examples of speech with a security systeminclude a person speaking to a doorbell, e.g., that includes amicrophone; a person speaking with a resident of the premises, e.g.,when the resident opens the door to speak with the person visiting thepremises; or speech by a delivery person that is related to delivery ofa package. Although an intruder might not necessarily intentionallycommunicate with a security system, for the purposes of thisspecification, speech by a person with a resident of the premises,speech detected substantially concurrently with detection of apredetermined environmental sound, and speech by an intruder can beconsidered a communication with a security system.

When a security system determines that the likelihood satisfies athreshold likelihood, the security system can maintain the encoding ofthe speech. For instance, the security system can maintain the encodingin a database, initiate a recording by a microphone, or both.

When the security system determines that the likelihood does not satisfythe threshold likelihood, e.g., and that the person was not likelycommunicating with the security system, the security system canobfuscate the person's voice, e.g., speech. This can include thesecurity system removing an encoding of the person's voice from an audiosignal that encoded the person's voice along with other noise, e.g.,background noise. This can include the security system determining toskip initiating a recording of the person's voice.

In general, one innovative aspect of the subject matter described inthis specification relates to determining whether to maintain at least aportion of an audio recording in memory, and can be embodied in methodsthat include the actions of detecting, by a security system for apremises, that a person who was within a threshold area for the premiseswas likely uttering a sound; determining, using data from one or moresensors physically located at the premises, a likelihood that the personwas communicating with the security system at the premises; determiningwhether the likelihood satisfies a threshold likelihood and that theperson's voice should not be obfuscated; and in response to determiningthat the likelihood satisfies the threshold likelihood and that theperson's voice should not be obfuscated, maintaining, in memory, anaudio signal i) that encodes the person's voice and ii) was captured bya microphone that was physically located at the premises.

In general, one innovative aspect of the subject matter described inthis specification relates to determining whether to maintain at least aportion of an audio recording in memory, and can be embodied in methodsthat include the actions of detecting, by a security system for apremises, that a person who was within a threshold area for the premiseswas likely uttering a sound; determining, using data from one or moresensors physically located at the premises, a likelihood that the personwas communicating with the security system at the premises; determiningwhether the likelihood satisfies a threshold likelihood and that theperson's voice should not be obfuscated; and in response to determiningthat the likelihood does not satisfy the threshold likelihood and thatthe person's voice should be obfuscated, obfuscating the person's voice.

Other embodiments of this aspect include corresponding computer systems,apparatus, computer program products, and computer programs recorded onone or more computer storage devices, each configured to perform theactions of the methods. A system of one or more computers can beconfigured to perform particular operations or actions by virtue ofhaving software, firmware, hardware, or a combination of them installedon the system that in operation causes or cause the system to performthe actions. One or more computer programs can be configured to performparticular operations or actions by virtue of including instructionsthat, when executed by data processing apparatus, cause the apparatus toperform the actions.

The foregoing and other embodiments can each optionally include one ormore of the following features, alone or in combination. Instead of orin addition to a threshold area, a threshold distance can be used. Insome examples, the one or more sensors are physically located at thepremises. However, this is optional. For instance, at least one of orall of the one or more sensors might not be physically located at thepremises. For example, one of the one or more sensors can be physicallylocated at a second premises adjacent to the premises, e.g., aneighboring property from which the security system receives the data.

In some implementations, detecting that the person who was within thethreshold area for the premises was likely uttering a sound can includedetecting, using video data captured by a camera that was physicallylocated at the premises, an image that depicts the person's lips moving.The method can include retrieving, from a database for the premises, anaudio signal encoding captured when the person was within the thresholdarea for the premises. Detecting that the person was likely uttering asound can include detecting that the audio signal likely encodes thevoice of the person who was within the threshold area for the premises.

In some implementations, detecting that the person who was within thethreshold area for the premises was likely uttering a sound can includedetecting, using audio data captured by a microphone that was physicallylocated at the premises, an encoding of the person's voice. Determiningthe likelihood that the person was communicating with the securitysystem at the premises can include determining, using the audio datacaptured by the microphone, the likelihood that the person wascommunicating with the security system at the premises.

In some implementations, determining the likelihood that the person wascommunicating with the security system at the premises can includedetermining, using voice recognition, whether a first signature for theperson's voice matches a second signature included in a database thatincludes one or more signatures, each signature of which is for a secondperson for which there is at least a second threshold likelihood thatthe second person will be within a second threshold area for thepremises. Determining whether the likelihood satisfies the thresholdlikelihood can include determining that the likelihood does not satisfythe threshold likelihood and that the person's voice should beobfuscated when the first signature matches the second signature.

In some implementations, determining the likelihood that the person wascommunicating with the security system at the premises can includedetermining, using voice recognition, whether a first signature for theperson's voice matches a second signature included in a database thatincludes one or more anonymized signatures, each signature of which isfor a second person for which there is at least a second thresholdlikelihood that the second person will be within a second threshold areafor the premises. Determining whether the likelihood satisfies thethreshold likelihood can include determining that the likelihood doesnot satisfy the threshold likelihood and that the person's voice shouldbe obfuscated when the first signature matches the second signature.

In some implementations, obfuscating the person's voice can includeremoving, from an audio signal captured by a microphone that wasphysically located at the premises, an encoding of the person's voice.The method can include maintaining, in the audio signal, an encoding ofbackground noise that is separate from the encoding of the person'svoice. Obfuscating the person's voice can include determining to skipinitiating a recording of the person's voice by a microphone that isphysically located at the premises.

In some implementations, the method can include detecting that theperson who was within the threshold area for the premises was likelyuttering a second sound; determining, using second data from the one ormore sensors, a second likelihood that the person was communicating withthe security system at the premises by way of the second sound;determining whether the second likelihood satisfies the thresholdlikelihood and that the person's voice for the second sound should notbe obfuscated; and in response to determining that the second likelihooddoes not satisfy the threshold likelihood and that the person's voicefor the second sound should be obfuscated, obfuscating the person'svoice for the second sound.

In some implementations, determining the likelihood that the person wascommunicating with the security system at the premises can includedetermining, using voice recognition, whether a first signature for theperson's voice matches a second signature included in a database thatincludes one or more signatures, each signature of which is for a secondperson for which there is at least a second threshold likelihood thatthe second person will be within a second threshold area for thepremises. Determining whether the likelihood satisfies the thresholdlikelihood can include determining that the likelihood satisfies thethreshold likelihood and that the person's voice should not beobfuscated when the first signature does not match the second signature.

In some implementations, determining the likelihood that the person wascommunicating with the security system at the premises can includedetermining, using voice recognition, whether a first signature for theperson's voice matches a second signature included in a database thatincludes one or more anonymized signatures, each signature of which isfor a second person for which there is at least a second thresholdlikelihood that the second person will be within a second threshold areafor the premises. Determining whether the likelihood satisfies thethreshold likelihood can include determining that the likelihoodsatisfies the threshold likelihood and that the person's voice shouldnot be obfuscated when the first signature does not match the secondsignature.

In some implementations, determining, using the data from the one ormore sensors, the likelihood that the person was communicating with thesecurity system at the premises can include determining one or more of:the likelihood that the person was speaking with a resident of thepremises; the likelihood that the person spoke within a threshold timeof a predetermined environmental sound detected by the security system;or the likelihood that the person is an intruder at the premises wholikely uttered the sound.

The subject matter described in this specification can be implemented invarious embodiments and may result in one or more of the followingadvantages. In some implementations, the systems and methods describedin this specification can reduce an amount of speech encoded in an audiosignal, a size of an audio signal, an amount of network bandwidthnecessary to transmit an audio signal, or a combination of these, byobfuscating a person's voice. In some implementations, the systems andmethods described in this specification can increase privacy, complywith privacy laws, or both, by obfuscating a person's voice.

In some implementations, the systems and methods described in thisspecification can increase a likelihood that relevant sounds maintainedin an audio signal are clearer, or easier to understand by obfuscating aperson's voice encoded in the audio signal. For instance, when the audiosignal encodes multiple sounds at the same time, obfuscating theencoding of the person's voice encoded in the audio signal, e.g.,removing the encoding, can make the other sounds encoded in the audiosignal clearer or easier to understand given that there are fewer soundsencoded at the same time in the audio signal.

In some implementations, the systems and methods described in thisspecification can improve the clarity of sounds maintained in an audiosignal by normalizing one or more of the sounds. For instance, thesystems and methods described in this document can normalize a person'svoice that is maintained in an audio signal when other sounds encoded inthe audio signal are louder than the person's voice.

The details of one or more implementations of the subject matterdescribed in this specification are set forth in the accompanyingdrawings and the description below. Other features, aspects, andadvantages of the subject matter will become apparent from thedescription, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example environment of a security system thatselectively obfuscates audio for a premises.

FIG. 2 depicts some examples of maintaining or obfuscating audio.

FIG. 3 is a flow diagram of a process for selectively obfuscating audio.

FIG. 4 is a diagram illustrating an example of a home monitoring system.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

FIG. 1 depicts an example environment 100 of a security system 104 thatselectively obfuscates audio for a premises 102. The security system 104can determine whether to obfuscate the audio given a likelihood that aperson is speaking with the security system 104 or that the securitysystem 104 might otherwise require the audio for later analysis. Theformer can occur when the person uses the security system 104 tocommunicate with another person at the premises 102 or to communicatedirectly with the security system 104, e.g., when dropping off apackage. The latter can occur when the security system 104 determinesthat the person might be trying to break into the premises 102, or inother appropriate situations.

For example, the security system 104 can include one or more sensors106, such as cameras 108 and microphones 110. In some examples, thesensors 106 can include other types of sensors. One example of a sensorcan include a smart doorbell 106 a. The smart doorbell 106 a can includea camera, a microphone, or both. In some examples, the smart doorbell106 a includes a microphone and the premises 102 has a separate camera108 a.

The security system 104 can receive data from the sensors 106. Thesecurity system 104 can analyze the sensor data as the security system104 receives the sensor data, e.g., in real time, after the securitysystem 104 receives the sensor data, e.g., offline, or a combination ofboth.

As part of the analysis, the security system 104 can analyze the sensordata from the sensors 106 to detect whether a person 118 a is within athreshold distance of, the threshold area for, or both, the premises102. The security system 104 can store data for the threshold distance,the threshold area, or both, as one of multiple threshold criteria 114.The threshold distance can be any appropriate distance, such as apredetermined distance from the premises 102, e.g., as defined by aradius extending from the center of the premises 102, a predetermineddistance from the edge of a yard in which the premises 102 is located,the range of one or more of the sensors 106, e.g., of the microphone110, or another appropriate distance. In some examples, thepredetermined distance can be defined by operator input, e.g., anadministrator for the security system 104 or a user of the securitysystem 104 such as the owner of the premises 102.

In some implementations, the threshold area can be any area in or arounda physical area around the premises 102. For instance, the thresholdarea can include an area defined around the premises 102 given thethreshold distance, e.g., the threshold area can include the thresholddistance, defined by the contours of a yard around the premises 102,defined by a distance from the contours of the yard, or a combination ofthese. In some examples, the threshold area can be an area that is notdefined by a threshold distance. For instance, the area can be in afront lawn on the premises 102, e.g., that includes a sidewalk thatapproaches a front door for the premises 102.

The threshold area can be determined using any appropriate process. Forinstance, the security system 104 or another system can determine one ormore threshold areas, e.g., based on an analysis of images for thepremises 102 that depict people near the premises. In some examples, thethreshold area can be a user defined area. For instance, a user devicecan receive user input that indicates an arbitrarily drawn area thatidentifies the boundaries of the threshold area. The user device canreceive the input using any appropriate process, e.g., in a userinterface, using a microphone for voice commands, or both.

For instance, the security system 104 can receive sensor data from thesmart doorbell 106 a and analyze the sensor data. While analyzing thesensor data, the security system 104 can determine that the sensor dataindicates that the person 118 a is within the threshold distance from,the threshold area for, or both, the premises 102. The security system104 can make this determination when a camera included in the smartdoorbell 106 a captures an image that depicts the person 118 a, when thesecurity system 104's analysis of an image captured by the smartdoorbell 106 a indicates that the person 118 a is within a predeterminedphysical distance of the premises 102, when an audio signal encoded bythe smart doorbell 106 a encodes speech or another utterance made by theperson 118 a, or a combination of two or more of these. In someexamples, the security system 104 can detect sounds encoded in the audiosignal such as the person humming a tune.

When the security system 104 determines that the person 118 a is notwithin the threshold distance from, the threshold area for, or both, thepremises 102, the security system 104 can discard sensor data of theperson 118 a, discard audio sensor data of the person's voice, notrecord audio sensor data of the person's voice, or perform anotherappropriate action. For instance, the security system 104 can discardany audio data, e.g., encoding any person's voice, when the respectiveperson is not within the threshold distance from, the threshold areafor, or both, the premises 102. The security system 104 can discard thesensor data and not perform any additional analysis on the sensor data,e.g., decide to skip determining a likelihood that the person wascommunicating with the security system 104.

When the security system 104 determines that the person 118 a is withinthe threshold distance from, the threshold area for, or both, thepremises 102, the security system can perform additional analysis of theperson 118 a, the sensor data, other sensor data for the person 118 a,or a combination of two or more of these. For instance, the securitysystem 104 can use sensor data from the sensors 106 to determine alikelihood that the person 118 a was communicating with the securitysystem 104. The security system 104 can determine this likelihood usingany appropriate process. The security system 104 can compare thelikelihood with a threshold likelihood, from the threshold criteria 114,to determine whether, what, or both, additional analysis to perform.

For example, the security system 104 can use image data to determine alikelihood that the person is speaking. The security system 104 can useimage data to determine whether another person is near, e.g., within asecond threshold distance of, the person.

For instance, the security system 104 receives image data from a secondcamera 108 b. The image data can depict a second person 118 b and athird person 118 c. At least some images included in the image data candepict the second person 118 b talking. By analyzing the images, thesecurity system 104 can determine that the second person 118 b is bothwithin the threshold distance of, the threshold area for, or both, thepremises 102 and talking. However, in this example, the security system104 can determine that the second person 118 b is not likelycommunicating with the security system 104 given the proximity of thesecond person 118 b to the third person 118 c, e.g., that a likelihoodthat the second person 118 b is communicating with the security system104 does not satisfy a threshold likelihood.

In some examples, the security system 104 can determine that a speakerwho is in close proximity to another person is likely communicating withthe security system 104. For instance, the security system 104 canperform speech recognition, voice recognition, or both, on an audiosignal that encodes the person's speech. In this example, the securitysystem 104 can analyze an audio signal that encodes the second person's118 b speech. The security system 104 can determine a likelihood thatthe second person 118 b is communicating with the security system 104using a result of this analysis, e.g., a likelihood that the secondperson is asking the security system 104 a question. The security system104 can then compare the likelihood with the threshold likelihood todetermine whether the likelihood satisfies the threshold likelihood,e.g., and the second person 118 b is likely communicating with thesecurity system 104.

The security system can use any appropriate data to determine thelikelihood. For instance, the security system can use video data; audiodata; data that indicates where the person is standing with respect tothe premises, e.g., if the person is within a threshold distance of adoor or a window of the premises 102; a voice signature for the person;a keyword or key phrase; data that indicates whether the person iscommunicating with another person; whether there is an alarm conditionat the premises 102; whether the sensor data indicates that a doorbellwas pressed; sensor data from a device at the premises 102, such as asmart phone or a vehicle; or a combination of two or more of these.

When using data from a smart phone, a vehicle, or another location baseddevice that can provide location data to the security system 104, thesecurity system 104 can determine a location of a person with thecorresponding location based device. The security system 104 can receivelocation data from the location based device to determine an approximatelocation of the device. The security system 104 can use the locationdata to determine whether captured sensor data likely was generated by aperson using the location based device, the location based deviceitself, e.g., when the device is playing music, or both. The securitysystem 104 can use the first likelihood that the captured data likelywas generated by the person using the location based device, thelocation based device itself, or both, to determine the secondlikelihood that a person was communicating with the security system 104.In some examples, the security system 104 can determine the secondlikelihood as the opposite percentage of the first likelihood, e.g.,second likelihood=(1−first likelihood).

In some implementations, the security system 104 can use one or morevoice signatures 116 when determining the likelihood. The voicesignatures 116 can include voice signatures for people who are likely tocommunicate with the security system 104, e.g., a resident of thepremises 102, people who are not likely to communicate with the securitysystem 104, e.g., a neighbor, or both. The security system 104 canrequire permission before adding a voice signature to the voicesignatures 116, e.g., permission from the person for whom the voicesignature was generated.

For example, the security system 104 can store voice signatures 116 forone or more people who are within the threshold area for, e.g., distancefrom, the premises 102 at least a threshold amount of time, e.g.,residents of the premises 102. When the security system 104 detects anaudio signal that encodes the voice of one of the people, using thevoice signatures, the security system 104 can access correspondingsettings for the voice signature to determine whether the securitysystem 104 should maintain or obfuscate the person's voice. A settingfor a resident of the premises 102 can indicate that the security system104 should maintain the person's voice in audio signals. A setting for aneighbor can indicate that the security system 104 should obfuscate theneighbor's voice, e.g., absent a separate trigger that causes thesecurity system 104 to determine otherwise, such as the security system104 determining that the neighbor spoke a key phrase, or triggered thesmart doorbell 106 a.

The security system 104 can analyze any appropriate data whendetermining the likelihood. The security system 104 can analyze the samedata that was analyzed when determining whether the person was withinthe threshold distance of, the threshold area for, or both, the premises102 when determining the likelihood that the person was communicatingwith the security system 104. The security system 104 can analyzedifferent data when determining the likelihood that the person wascommunicating with the security system 104 than the data analyzed whendetermining whether the person was within the threshold distance of, thethreshold area for, or both, the premises 102.

Once the security system 104 determines a likelihood that the person 118a-b was communicating with the security system 104, the security system104 can compare the likelihood with the threshold likelihood todetermine whether the likelihood satisfies the threshold likelihood. Thelikelihood can satisfy the threshold likelihood when the likelihood isgreater than, equal to, or either greater than or equal to the thresholdlikelihood.

When the likelihood satisfies the threshold likelihood, the securitysystem 104 can determine to maintain an encoding of the person's voicein memory. For instance, the security system or another system caninclude a database of voice recordings.

FIG. 2 depicts some examples of maintaining 200 or obfuscating 202audio. For example, the security system 104 can determine to send aninstruction 204 to a microphone to cause the microphone to record theperson's voice. The recording can create a new audio signal that encodesthe person's voice or can continue creation of a prior audio signal thatencodes the person's voice, e.g., a portion of which the security system104 analyzed previously as described above. The security system 104 candetermine to maintain 206, in a database 208, the audio signal thatencodes the person's 118 a-b voice. This encoding can be of the personspeaking, or the person making another utterance, such as humming. Insome examples, the security system 104 can treat a person's singing orotherwise uttering words as speaking. The database can be part of thesecurity system or another system.

Returning to FIG. 1 , when the likelihood does not satisfy the thresholdlikelihood, the security system 104 can determine to obfuscate anencoding of the person's voice. The security system 104 can obfuscatingthe encoding of the person's voice using any appropriate process. Insome examples, the security system 104 can determine a process to usewhen obfuscating the encoding of the person's voice depending on a typeof the encoding, a source of the encoding, e.g., a microphone or adatabase, a time duration between when the security system 104 performsits analysis and the encoding was captured, a predicted type of soundincluded in the encoding, e.g., speech, singing, or humming, or acombination of these.

For instance, the security system 104 can determine to use a firstobfuscation process for a first type of encoding and a second, differentobfuscation process for a second, different type of encoding. Someexamples of encoding types can include an encoding received from amicrophone, an encoding stored in a database, e.g., at the securitysystem 104, or an encoding stored in a long term memory, e.g., in adatabase on a system separate from the security system 104.

The security system 104 can determine to use a first obfuscation processfor a first time duration between the security system's 104 analysis andcapture of the encoding or to use a second, different obfuscationprocess for a second, different time duration. The security system 104can compare a current duration with a threshold duration to determinewhether the current duration corresponds to the first time duration,e.g., a first range, or the second, different time duration, e.g., asecond range. For example, the security system 104 can use a firstobfuscation process that discards the encoding when the time duration isshorter and a second obfuscation process that removes the encoding froma database when the time duration is longer, e.g., and the encoding wasstored in a database during that longer time period.

The security system 104 can use a predicted type of sound to determinethe obfuscation process. For instance, the security system 104 can use afirst obfuscation process, e.g., that is faster, to obfuscate a person'svoice when the person was humming. This can include removing anycharacteristics from the encoding that could be used to personallyidentify the person 118 a. The security system 104 can use a secondobfuscation process, e.g., that is slower, to obfuscate a person's voicewhen the person is singing. This can include the security system 104removing, from the encoding, the portion that encodes the person'svoice. This can include maintaining, in the encoding, other noise thatencodes other sounds, e.g., when the other sounds are not anotherperson's voice that might also need to be obfuscated.

Returning to FIG. 2 , Some example obfuscation processes can includesending 210 an instruction to cause a microphone to stop or otherwisenote record audio, deleting 212 the encoding of the person's voice,removing 214, from the encoding, the portion of the encoding thatencodes the person's voice, removing 216, from the encoding, the timesegment in which the person's voice was encoded, or a combination of twoor more of these. Removing the portion of the encoding that encodes theperson's voice can include the security system removing or otherwisecanceling out the bits 218 that encode the person's voice whilemaintaining, for the same time segments that encode the person's voice,one or more other bits 220 that encode other sounds. Removing the timesegment can include determining, for the encoding that spans multipletime segments, the time segment 222 during which the person's voice isencoded and removing that time segment while maintaining other timesegments 224, e.g., that can each have different lengths.

Returning to FIG. 1 , in some implementations, the threshold criteria114 can include two or more thresholds for a particular value. Forexample, the security system 104 can maintain in the threshold criteria114 two or more threshold distances, two or more threshold areas, two ormore threshold likelihoods, or a both. The security system 104 canselect a threshold to use from the two or more threshold using data forthe scenario that the security system 104 is analyzing. A scenario caninclude an instance of a person uttering a sound, whether the person isalone or in a group of people. When a person is part of a group ofpeople, there can be a single scenario for each person and correspondingdata for the scenario.

The security system 104 can determine which of the two or morethresholds to use during any particular scenario with configurationdata, e.g., included in the threshold criteria. The configuration datacan indicate that the security system 104 can use different thresholdsduring different times of day, different days of week, different weatherconditions, given different input data, or a combination of two or moreof these.

In some examples, the configuration data can indicate that the securitysystem 104 should use a different threshold given different sensor data,as a type of input data, received from the sensors 106. For instance,when the security system 104 receives sensor data that indicates thattwo people are talking, one or more people are walking toward thepremises 102, one or more people are walking away from the premises 102,that a person depicted in an image is likely an emergency servicesperson, or a combination of these, the security system 104 can selectfrom different thresholds included in the threshold criteria 114.

In this way, the security system 104 can select a first thresholdcriteria 114 during the night and a second, different threshold criteria114 during the day, and perform different actions, e.g., determine thatthe threshold is or is not satisfied, even though all other data are thesame for the two scenarios. In some examples, the security system 104can perform different actions when sensor data for different numbers ofpeople are captured even though that data is captured during the sametime of day, day of week, or both, given the use of different thresholdsfor the different numbers of people.

In some implementations, the security system 104 can determine whetherthe premises 102, the security system 104, or both, are in an alarmstate, an armed state, a disarmed state, or a combination of two or moreof these. Using this determination, the security system 104 can selectdifferent thresholds; determine whether to skip determining a likelihoodor whether a threshold is satisfied; or a combination of both. Forinstance, when the security system 104 determines that the premises 102,the security system 104, or both, are in an armed state or a disarmedstate, the security system 104 can select a different threshold from thethreshold criteria 114 than the security system 104 would select werethe other state active.

In some examples, the security system 104 can determine to skipdetermining a likelihood that the person 118 was communicating with thesecurity system 104. For instance, in some implementations, when thesecurity system 104 detects a person who is malicious, e.g., trying tobreak into the premises 102, the security system 104 can determine toinitiate an alarm state. When in an alarm state, the security system 104can determine to skip determining a likelihood that the person is tryingto communicate with the security system 104, skip determining whetherthe likelihood satisfies a threshold likelihood, or both. In theseimplementations, the security system 104 can maintain an encoding of theperson's voice. The security system 104 can perform any otherappropriate action, such as notify security personnel, notify thepolice, trigger an alarm at the premises 102, or a combination of these.

In some implementations, the security system 104 can perform someanalysis for a person multiple times. For instance, as the person 118 aapproaches the premises 102, the security system 104 can make a firstdetermination whether to obfuscate the person's voice for a first timeperiod. The first time period can be while some of the sensors 106capture data for the person 118 a and a distance between the person andthe premises 102 does not satisfy a threshold distance, the thresholdarea, or both. As part of the first determination, the security system104 can determine to obfuscate the person's voice.

The security system 104 can continue to make obfuscation decisions whilethe person approaches the house, moves, speaks, performs other actions,or a combination of two or more of these. When the person's distancefrom the premises 102 satisfies the threshold distance, or the person'slocation satisfies the threshold area, or both, the security system 104can make a second determination whether to obfuscate the person's voicefor a second time period. Although the second time period is after thefirst time period, there can be other time periods, otherdeterminations, or both, between the two time periods.

In this example, the second time period can be a time during which theperson 118 a is within the threshold distance from, the threshold areafor, or both, the premises 102. This can be when the person 118 a isnear a landing by a door to the premises 102, near a package drop offarea, or at another appropriate location.

As part of the second determination, the security system 104 candetermine to maintain an encoding of the person's voice. For example,the security system 104 can determine to store the encoding receivedfrom the microphone 110 in a memory, e.g., in a database.

In some examples, the security system 104 can determine to maintain anencoding of the person's 118 a voice when the person 118 a performs apredetermined action. The predetermined action can be any appropriateaction, such as triggering a doorbell. In these examples, the premises102 can have a sign or other notification, e.g., an electronicnotification using near-field communication, that indicates thatperformance of the predetermined action will cause the security system104 to maintain an encoding of the person's 118 a voice.

The security system 104 can analyze data in real time, offline, or both.For instance, the security system 104 can analyze sensor data as it iscaptured by one of the sensors 106 and before the sensor data is storedin permanent memory, e.g., while the person 118 a is currently at thepremises 102. In some examples, the security system 104 can analyzesensor data after it is captured by one of the sensors 106 and stored inpermanent memory, e.g., after the person 118 a left an area around thepremises 102, entered the premises 102, or both.

When the security system 104 analyzes data before it is stored inpermanent memory, the security system 104 can reduce network traffic tothe permanent memory, or an amount of the memory used, by determiningwhether to obfuscate a portion of an audio signal that encodes aperson's voice, by obfuscating a portion of an audio signal that encodesa person's voice, or both. For instance, by obfuscating the portion ofthe audio signal, the security system 104 can reduce a size of the audiosignal such that transmission of the reduced size audio signal reducesan amount of network bandwidth used to transmit the audio signal to thepermanent memory. The network can be a network that connects thesecurity system 104 to another system, connects various components ofthe security system 104, or a combination of both. By obfuscating theportion of the audio signal, the security system 104 can reduce anamount of the memory required to store the audio signal.

The security system 104 can be physically located at the any appropriatelocation. For instance, at least a portion of the security system 104,e.g., the sensors 106, can be physically located at the premises 102. Atleast a portion of the security system 104 can be physically locatedsomewhere other than the premises 102, e.g., at a computing center.

Although some of the examples refer to analysis of data give that theperson “is” doing something, these examples can also apply to situationsin which the person “was” doing the same thing. For instance, thesecurity system 104 can analyze sensor data to determine whether theperson “was” within the threshold distance of, the threshold area for,or both, the premises 102, whether a likelihood that the person wascommunicating with the security system at the premises satisfies athreshold likelihood, or both, while the person is still within thethreshold distance of, the threshold area for, or both, the premises102, e.g., shortly after the person spoke, triggering analysis by thesecurity system 104.

The security system 104 is an example of a system implemented ascomputer programs on one or more computers in one or more locations, inwhich the systems, components, and techniques described in thisspecification are implemented. The location based devices can includepersonal computers, mobile communication devices, and other devices thatcan send and receive location data over a network. The network (notshown), such as a local area network (“LAN”), wide area network (“WAN”),a nearfield connection, the Internet, or a combination thereof, connectsthe location based devices, the security system 104, multiple componentsof the security system 104, or a combination of two or more of these.The components of the security system can include the sensors 106, thecameras 108, the microphone 110, and one or more computers thatimplement the security system 104, the communication prediction engine112, or both. The one or more computers can be separate from the sensors106 when the sensors 106 are physically located throughout the premises102. The one or more computers that implement the security system 104can be physically remote from the premises 102, at the premises 102, ora combination of both. The security system 104 may use a single servercomputer or multiple server computers operating in conjunction with oneanother, including, for example, a set of remote computers deployed as acloud computing service.

The security system 104 can include several different functionalcomponents, including the communication prediction engine 112. Thecommunication prediction engine 112 can include one or more dataprocessing apparatuses. For instance, the communication predictionengine 112 can include one or more data processors and instructions thatcause the one or more data processors to perform the operationsdiscussed herein.

In some implementations, one or more of the functional components of thesecurity system 104, e.g., the communication prediction engine 112, thethreshold criteria 114, or the voice signatures 116, can be implementedon one or more of the sensors 106. For instance, a first sensor canimplement a first functional component, e.g., a first communicationprediction engine, and a second sensor can implement a second functionalcomponent, e.g., a second communication prediction engine or the voicesignatures or both.

The various functional components of the security system 104 may beinstalled on one or more computers as separate functional components oras different modules of a same functional component. For example, thecommunication prediction engine 112 can be implemented as a computerprogram installed on one or more computers in one or more locations thatare coupled to each through a network. In cloud-based systems forexample, these components can be implemented by individual computingnodes of a distributed computing system.

FIG. 3 is a flow diagram of a process 300 for selectively obfuscatingaudio. For example, the process 300 can be used by the security system104 from the environment 100.

A security system detects that a person, who was within a threshold areafor the premises, was likely uttering a sound (302). The sounds caninclude speaking, singing, humming, or other appropriate sounds. Forinstance, the security system can receive data that indicates that theperson was likely speaking, such as speech data. In some examples, thesecurity system can detect a person that was likely speaking. For thepurposes of this specification, speech can include singing and othersounds that include utterances of words.

In some examples, the security system can receive sensor data frommultiple devices. The security system can receive first data from acamera and receive second data from a microphone. The security systemcan analyze the second data and determine that the second data encodesspeech. The security system can analyze the first data and determinethat one or more pictures included in the first data depict the person.The security system can determine that the first data was capturedsubstantially concurrently with the second data. The security system candetermine that the first data depicts the person's lips moving. Inresponse to determining that the first and second data were capturedsubstantially concurrently, and that the first data depicts the person'slips moving, the security system can detect that the person was likelyuttering a sound.

The security system determines whether the security system was in analarm state when the person was likely uttering a sound (304). Forinstance, the security system can determine whether to use a first,lower threshold for when the security system is in an alarm state or asecond, higher threshold for when the security system is not in an alarmstate. The security system can have multiple threshold to reduce anamount of speech encoded in corresponding audio signals, and memoryrequired to store the audio signals, by reducing an amount of speechthat will be encoded in the audio signals when the security system isnot in the alarm state and uses the second, higher threshold. When thesecurity system is in the alarm state, the security system might be morelikely to require an audio signal encoding speech and using the lowerthreshold during this time periods can increase the probability that thesecurity system will encode speech in the audio signal when required.

The security system selects a first, lower threshold as a thresholdvalue (306). For instance, when the security system determines that thesecurity system was in the alarm state when the person was likelyuttering a sound, the security system can select the first, lowerthreshold to use during further analysis.

The security system selects a second, higher threshold as a thresholdvalue (308). For example, when the security system determines that thesecurity system was not in the alarm state when the person was likelyuttering a sound, the security system can select the second, higherthreshold to use during further analysis.

The security system determines a likelihood that the person wascommunicating with a security system at the premises (310). The securitysystem can use any combination of multiple different parameters todetermine the likelihood. In this specification, the likelihood that theperson was communicating with the security system can also include alikelihood that the person was trying to break into the premises.

The parameters can be any appropriate parameters for analysis of whetherthe person was trying to communicate with the security system, such asenvironmental parameters. The parameters can include data that indicateswhere the person was standing with respect to the premises. Theparameters can include data that indicates whether the security systemrecognizes the person, e.g., using facial recognition, voicerecognition, or both. This can occur for an owner or another resident ofthe premises, e.g., who opted in to use of facial recognition by thesecurity system.

The parameters can include a direction in which the person is facing.For instance, the security system can determine a higher likelihood fora person who is facing the premises or a predetermined area of thepremises. The predetermined area of the premises can include amicrophone or another area identified for communication with thesecurity system, e.g., a call box.

The parameters can include a number of people who are standing together,whether, how, or both, the people are interacting, or a combination ofthese. For instance, the security system can determine a lowerlikelihood when a person who is likely uttering a sound is with one ormore other people than if the person were alone.

The parameters can include one or more visual cues depict in an image.The visual cues can include hand movements, interaction with objects atthe premises, e.g., a doorbell, or both.

In some implementations, the security system can analyze image data andaudio data to determine whether the movement of the person's lips matchaudio encoded in an audio signal. The parameters can include a result ofthis analysis. When the movement matches the encoded audio, the securitysystem can determine a higher likelihood. When the movement does notmatch the encoded audio, the system can determine a lower likelihood,e.g., because the audio likely came from another source other than theperson.

In some implementations, the security system can determine a cadence ofa conversation between people. The security system can use the cadenceto determine the likelihood, e.g., as one of the parameters.

The parameters can include environmental parameters, such as parametersthat represent other sounds encoded in the audio signal. The othersounds can include the sounds of animals, a window breaking, glassbreaking, a rock hitting another object, a vehicle, or any otherappropriate sound. The security system can determine a higher likelihoodwhen the other sounds include the sound of a window breaking than wouldotherwise be determined, e.g., all other parameters being the same.

In some implementations, the parameters can indicate that if an audiosignal, or multiple audio signals captured substantially concurrently,e.g., by a single microphone or multiple microphones, encode data for apredetermined environmental parameter along with a person's voice, thatthe security system should maintain the encoding of the person's voice,e.g., that there is a higher likelihood that the person wascommunicating with the security system than if the predeterminedenvironmental parameter was not encoded. This can occur when thesecurity system captured two audio signals, a first that encodes awindow breaking and a second of a person's voice.

The security system determines whether the likelihood satisfies thethreshold likelihood value (312). For instance, the security system cancompare the likelihood with the threshold likelihood. The securitysystem can use a result of the comparison to determine whether thelikelihood satisfies the threshold likelihood. In some examples, thelikelihood satisfies the threshold likelihood when the likelihood isgreater than, equal to, or either greater than or equal to the thresholdlikelihood. In some examples, the likelihood satisfies the thresholdlikelihood when the likelihood is less than, equal to, or either lessthan or equal to the threshold likelihood.

The security system maintains, in memory, an audio signal that encodesthe person's voice (314). For example, in response to determining thatthe likelihood satisfies the threshold likelihood, the security systemcan maintain the audio signal in memory. If the audio signal is alreadystored in memory, e.g., in a database, the security system can determineto keep the audio signal in memory. If the audio signal is not alreadystored in a database, the security system can determine to store theaudio signal in a database. In response, the security system can storethe audio signal that encodes the person's voice in the database.

The security system can determine to maintain the person's encoded inthe audio signal when the security system determined a likelihood usingenvironmental sounds, such as the sound of a breaking window. Forinstance, upon detecting a breaking window, the security system candetermine a likelihood that would be higher than if the security systemhad not detected the breaking window. This can occur when there is ahigher chance that the person might be associated with the breakingwindow and the audio signal encoding the person's voice can be used foranalysis related to the breaking window.

The security system obfuscates the person's voice (316). For instance,the security system can obfuscate the person's voice in response todetermining that the likelihood does not satisfy the thresholdlikelihood.

In some examples, the security system can obfuscate the person's voicein response to determining that the person's voice matches a voicesignature for which the security system should obfuscate voices. Thevoice signature can be a neighbor's voice signature, a child's voicesignature, or any other appropriate voice signature.

In some examples, the security system can analyze voice signatures todetermine one or more parameters for analysis of a likelihood, thethreshold value, or both. For instance, the security system candetermine whether the encoded voice matches a voice signature for whichdifferent parameters are used to determine a likelihood that the personwas communicating with the security system compared to people whosevoice does not match a voice signature with different parameters. Theparameters can indicate a different distance from the premises, aparticular direction in which the person should be facing, or any otherappropriate parameters for determining a likelihood that the person wascommunicating with the security system. In this way, the security systemcan use a shorter distance or a different direction in which the personis facing for a neighbor, a child, or another appropriate personcompared to someone else, e.g., a delivery person.

In some examples, the security system can determine to remove anencoding of the person's voice, or skip maintaining an encoding of theperson's voice. The security system can determine to remove the encodingof the person's voice from a memory, e.g., a database, from an encodingthat includes one or more other sounds, or both. The security system candetermine to skip maintaining the encoding of the person's voice whenthe security system receives the encoding from a microphone. In thisexample, the security system can discard the encoding without storingthe encoding in memory.

The order of steps in the process 300 described above is illustrativeonly, and selectively obfuscating the audio can be performed indifferent orders. For example, the security system can determine thelikelihood that the person was communicating with the security system(e.g., step 310) and then determine whether the security system was inan alarm state (e.g., step 304).

In some implementations, the process 300 can include additional steps,fewer steps, or some of the steps can be divided into multiple steps.For example, the security system can select the threshold value usingother data, e.g., including or other than whether the security systemwas in an alarm state.

In some implementations, the security system can perform steps 302, 310,312, and either step 314 or 316 without performing the other steps inthe process 300. In some examples, the security system can perform steps302, 304, 308, 312, and 316 without performing the other steps in theprocess 300. In some examples, the security system can perform steps302, 304, 308, 312, and 314 without performing the other steps in theprocess 300. In some implementations, the security system can performsteps 302, 304, 306, 310, 312, and either step 314 or 316 withoutperforming the other steps in the process 300.

In some implementations, when the person is in a group of people, thesecurity system can determine likelihoods for each person in the group.As a result, the security system can determine to maintain audio for atleast one person in the group and determine to obfuscate audio for atleast another person in the group. In these implementations, thesecurity system can perform the process 300 multiple times, includingperforming some of the steps in the process 300 for a first person andsome of the steps in the process 300 for a second, different person. Thesecurity system can perform at least some of the steps for each of thepeople, e.g., step 310.

In some implementations, the security system, or a device in thesecurity system such as a microphone, can encode two audio signals forthe same time period. The first audio signal can encode speech, e.g.,either for a person or multiple people. The second audio signal canencode other sounds, e.g., background sounds such as animals, vehicles,or both. The security system can analyze the first audio signal todetermine whether to obfuscate a portion of the audio signal.

In some implementations, when more than one person is detected, e.g., bythe security system or a device in the security system, the securitysystem can encode one audio signal for each person. The security systemcan analyze each audio signal and determine whether to obfuscate theperson's voice encoded in the audio signal.

In some implementations, the security system can receive the audiosignal encoding the person's voice as part of a process, e.g., abackground process, that periodically samples audio from the environmentaround the premises. In these implementations, the security system cananalyze the audio signal and determine whether to initiate recordingaudio by a microphone, e.g., to record more audio from the environment.

For instance, a microphone at the premises can sample audio from theenvironment and send the sample audio to the security system, e.g., acommunication prediction engine. The security system can analyze thesampled audio to determine a likelihood that the audio encodes aperson's voice. Upon determining that the audio encodes a person'svoice, the security system can send an instruction to the microphone oranother microphone to cause the receiving microphone to recordadditional audio from the environment.

In some implementations, the security system can determine to maintainsounds that we likely generated by an object that is not depicted in animage captured by a camera, e.g., when the images captured substantiallyconcurrently with detection of the sound do not depict the object. Forinstance, the security system can analyze an audio signal that encodes asound and images captured substantially concurrently with the encodingof the sound. The security system can determine, from the analysis ofthe audio signal and the images, that the sound was likely generated byan object, e.g., a person or an animal or an inanimate object, that wasnot depicted in any of the images.

The security system can analyze other data captured substantiallyconcurrently with the encoding of the sound. For instance, the securitysystem can determine that one of the images depicts a person who was nottalking when the sound was encoded. The security system can determinethat the person was talking after the sound finished, e.g., that theperson is talking to another person who spoke the sound and is out of afield of view of the cameras in the security system. The security systemcan determine whether the person is a resident of the premises or theperson's speech should otherwise be recorded, e.g., that the person islikely speaking with the security system. If so, the security system candetermine to maintain the sound spoken by the other person who was notdepicted in any of the images.

In some examples, the security system can determine to maintain thesound that was likely generated by an object not depicted in any of theimages based on a type of the sound. For instance, the security systemcan determine that the sound satisfies an environmental parameter forsounds that should be maintained. Environmental parameters can includeparameters that represent a breaking window, breaking glass, a caralarm, or one object crashing into another, to name a few examples.

In some implementations, the security system can normalize one or moresounds maintained in an audio signal. For instance, when the securitysystem determines to maintain an encoding of a person's voice in anaudio signal, the security system can determine a loudness of theperson's voice. The security system can determine one or more loudnessesof other sounds encoded in the audio signal. The security system cancompare the loudness of the person's voice with at least one of the oneor more loudnesses for the other sounds encoded in the audio signal todetermine a comparison result.

If the comparison result satisfies a threshold, the security system cannormalize the encoding of the person's voice, e.g., increase theloudness of the person's voice in the audio signal. The comparisonresult can satisfy the threshold when the loudness is less than athreshold percentage of the loudnesses, when the loudness is less than apredetermined quantity of the loudnesses, e.g., one or more, or in otherappropriate situations.

If the comparison result does not satisfy the threshold, the securitysystem can maintain the encoding of the person's voice in the audiosignal. For example, the security system can maintain the encoding ofthe person's voice without adjusting the loudness of the person's voicein the audio signal.

For situations in which the systems discussed here collect personalinformation about users, or may make use of personal information, theusers may be provided with an opportunity to control whether programs orfeatures collect personal information (e.g., information about a user'ssocial network, social actions or activities, profession, a user'spreferences, or a user's current location), or to control whether and/orhow to receive content from the security system that may be morerelevant to the user. In addition, certain data may be anonymized in oneor more ways before it is stored or used, so that personallyidentifiable information is removed. For example, a user's identity maybe anonymized so that no personally identifiable information can bedetermined for the user, or a user's geographic location may begeneralized where location information is obtained (such as to a city,ZIP code, or state level), so that a particular location of a usercannot be determined. Thus, the user may have control over howinformation is collected about him or her and used by a security system.

FIG. 4 is a diagram illustrating an example of a home monitoring system400. The home monitoring system 400 includes a network 405, a controlunit 410, one or more user devices 440 and 450, a monitoring server 460,and a central alarm station server 470. In some examples, the network405 facilitates communications between the control unit 410, the one ormore user devices 440 and 450, the monitoring server 460, and thecentral alarm station server 470.

The network 405 is configured to enable exchange of electroniccommunications between devices connected to the network 405. Forexample, the network 405 may be configured to enable exchange ofelectronic communications between the control unit 410, the one or moreuser devices 440 and 450, the monitoring server 460, and the centralalarm station server 470. The network 405 may include, for example, oneor more of the Internet, Wide Area Networks (WANs), Local Area Networks(LANs), analog or digital wired and wireless telephone networks (e.g., apublic switched telephone network (PSTN), Integrated Services DigitalNetwork (ISDN), a cellular network, and Digital Subscriber Line (DSL)),radio, television, cable, satellite, or any other delivery or tunnelingmechanism for carrying data. Network 405 may include multiple networksor subnetworks, each of which may include, for example, a wired orwireless data pathway. The network 405 may include a circuit-switchednetwork, a packet-switched data network, or any other network able tocarry electronic communications (e.g., data or voice communications).For example, the network 405 may include networks based on the Internetprotocol (IP), asynchronous transfer mode (ATM), the PSTN,packet-switched networks based on IP, X.25, or Frame Relay, or othercomparable technologies and may support voice using, for example, VoIP,or other comparable protocols used for voice communications. The network405 may include one or more networks that include wireless data channelsand wireless voice channels. The network 405 may be a wireless network,a broadband network, or a combination of networks including a wirelessnetwork and a broadband network.

The control unit 410 includes a controller 412 and a network module 414.The controller 412 is configured to control a control unit monitoringsystem (e.g., a control unit system) that includes the control unit 410.In some examples, the controller 412 may include a processor or othercontrol circuitry configured to execute instructions of a program thatcontrols operation of a control unit system. In these examples, thecontroller 412 may be configured to receive input from sensors, flowmeters, or other devices included in the control unit system and controloperations of devices included in the household (e.g., speakers, lights,doors, etc.). For example, the controller 412 may be configured tocontrol operation of the network module 414 included in the control unit410.

The network module 414 is a communication device configured to exchangecommunications over the network 405. The network module 414 may be awireless communication module configured to exchange wirelesscommunications over the network 405. For example, the network module 414may be a wireless communication device configured to exchangecommunications over a wireless data channel and a wireless voicechannel. In this example, the network module 414 may transmit alarm dataover a wireless data channel and establish a two-way voice communicationsession over a wireless voice channel. The wireless communication devicemay include one or more of a LTE module, a GSM module, a radio modem, acellular transmission module, or any type of module configured toexchange communications in one of the following formats: LTE, GSM orGPRS, CDMA, EDGE or EGPRS, EV-DO or EVDO, UMTS, or IP.

The network module 414 also may be a wired communication moduleconfigured to exchange communications over the network 405 using a wiredconnection. For instance, the network module 414 may be a modem, anetwork interface card, or another type of network interface device. Thenetwork module 414 may be an Ethernet network card configured to enablethe control unit 410 to communicate over a local area network and/or theInternet. The network module 414 also may be a voice band modemconfigured to enable the alarm panel to communicate over the telephonelines of Plain Old Telephone Systems (POTS).

The control unit system that includes the control unit 410 includes oneor more sensors. For example, the monitoring system 400 may includemultiple sensors 420. The sensors 420 may include a lock sensor, acontact sensor, a motion sensor, or any other type of sensor included ina control unit system. The sensors 420 also may include an environmentalsensor, such as a temperature sensor, a water sensor, a rain sensor, awind sensor, a light sensor, a smoke detector, a carbon monoxidedetector, an air quality sensor, etc. The sensors 420 further mayinclude a health monitoring sensor, such as a prescription bottle sensorthat monitors taking of prescriptions, a blood pressure sensor, a bloodsugar sensor, a bed mat configured to sense presence of liquid (e.g.,bodily fluids) on the bed mat, etc. In some examples, the healthmonitoring sensor can be a wearable sensor that attaches to a user inthe home. The health monitoring sensor can collect various health data,including pulse, heart-rate, respiration rate, sugar or glucose level,bodily temperature, or motion data. The sensors 420 can also include aradio-frequency identification (RFID) sensor that identifies aparticular article that includes a pre-assigned RFID tag.

The control unit 410 communicates with the home automation controls 422and a camera 430 to perform monitoring. The home automation controls 422are connected to one or more devices that enable automation of actionsin the home. For instance, the home automation controls 422 may beconnected to one or more lighting systems and may be configured tocontrol operation of the one or more lighting systems. Also, the homeautomation controls 422 may be connected to one or more electronic locksat the home and may be configured to control operation of the one ormore electronic locks (e.g., control Z-Wave locks using wirelesscommunications in the Z-Wave protocol). Further, the home automationcontrols 422 may be connected to one or more appliances at the home andmay be configured to control operation of the one or more appliances.The home automation controls 422 may include multiple modules that areeach specific to the type of device being controlled in an automatedmanner. The home automation controls 422 may control the one or moredevices based on commands received from the control unit 410. Forinstance, the home automation controls 422 may cause a lighting systemto illuminate an area to provide a better image of the area whencaptured by a camera 430.

The camera 430 may be a video/photographic camera or other type ofoptical sensing device configured to capture images. For instance, thecamera 430 may be configured to capture images of an area within abuilding or home monitored by the control unit 410. The camera 430 maybe configured to capture single, static images of the area or videoimages of the area in which multiple images of the area are captured ata relatively high frequency (e.g., thirty images per second) or both.The camera 430 may be controlled based on commands received from thecontrol unit 410.

The camera 430 may be triggered by several different types oftechniques. For instance, a Passive Infra-Red (PIR) motion sensor may bebuilt into the camera 430 and used to trigger the camera 430 to captureone or more images when motion is detected. The camera 430 also mayinclude a microwave motion sensor built into the camera and used totrigger the camera 430 to capture one or more images when motion isdetected. The camera 430 may have a “normally open” or “normally closed”digital input that can trigger capture of one or more images whenexternal sensors (e.g., the sensors 420, PIR, door/window, etc.) detectmotion or other events. In some implementations, the camera 430 receivesa command to capture an image when external devices detect motion oranother potential alarm event. The camera 430 may receive the commandfrom the controller 412 or directly from one of the sensors 420.

In some examples, the camera 430 triggers integrated or externalilluminators (e.g., Infra-Red, Z-wave controlled “white” lights, lightscontrolled by the home automation controls 422, etc.) to improve imagequality when the scene is dark. An integrated or separate light sensormay be used to determine if illumination is desired and may result inincreased image quality.

The camera 430 may be programmed with any combination of time/dayschedules, system “arming state”, or other variables to determinewhether images should be captured or not when triggers occur. The camera430 may enter a low-power mode when not capturing images. In this case,the camera 430 may wake periodically to check for inbound messages fromthe controller 412. The camera 430 may be powered by internal,replaceable batteries, e.g., if located remotely from the control unit410. The camera 430 may employ a small solar cell to recharge thebattery when light is available. The camera 430 may be powered by thecontroller's 412 power supply if the camera 430 is co-located with thecontroller 412.

In some implementations, the camera 430 communicates directly with themonitoring server 460 over the Internet. In these implementations, imagedata captured by the camera 430 does not pass through the control unit410 and the camera 430 receives commands related to operation from themonitoring server 460.

The system 400 also includes thermostat 434 to perform dynamicenvironmental control at the home. The thermostat 434 is configured tomonitor temperature and/or energy consumption of an HVAC systemassociated with the thermostat 434, and is further configured to providecontrol of environmental (e.g., temperature) settings. In someimplementations, the thermostat 434 can additionally or alternativelyreceive data relating to activity at a home and/or environmental data ata home, e.g., at various locations indoors and outdoors at the home. Thethermostat 434 can directly measure energy consumption of the HVACsystem associated with the thermostat, or can estimate energyconsumption of the HVAC system associated with the thermostat 434, forexample, based on detected usage of one or more components of the HVACsystem associated with the thermostat 434. The thermostat 434 cancommunicate temperature and/or energy monitoring information to or fromthe control unit 410 and can control the environmental (e.g.,temperature) settings based on commands received from the control unit410.

In some implementations, the thermostat 434 is a dynamicallyprogrammable thermostat and can be integrated with the control unit 410.For example, the dynamically programmable thermostat 434 can include thecontrol unit 410, e.g., as an internal component to the dynamicallyprogrammable thermostat 434. In addition, the control unit 410 can be agateway device that communicates with the dynamically programmablethermostat 434. In some implementations, the thermostat 434 iscontrolled via one or more home automation controls 422.

A module 437 is connected to one or more components of an HVAC systemassociated with a home, and is configured to control operation of theone or more components of the HVAC system. In some implementations, themodule 437 is also configured to monitor energy consumption of the HVACsystem components, for example, by directly measuring the energyconsumption of the HVAC system components or by estimating the energyusage of the one or more HVAC system components based on detecting usageof components of the HVAC system. The module 437 can communicate energymonitoring information and the state of the HVAC system components tothe thermostat 434 and can control the one or more components of theHVAC system based on commands received from the thermostat 434.

The system 400 includes security system 457. The security system 457 canbe computing devices (e.g., a computer, microcontroller, FPGA, ASIC, orother device capable of electronic computation) capable of receivingdata related to the security system and communicating electronicallywith the monitoring system control unit 410.

In some examples, the system 400 further includes one or more roboticdevices 490. The robotic devices 490 may be any type of robots that arecapable of moving and taking actions that assist in home monitoring. Forexample, the robotic devices 490 may include drones that are capable ofmoving throughout a home based on automated control technology and/oruser input control provided by a user. In this example, the drones maybe able to fly, roll, walk, or otherwise move about the home. The dronesmay include helicopter type devices (e.g., quad copters), rollinghelicopter type devices (e.g., roller copter devices that can fly andalso roll along the ground, walls, or ceiling) and land vehicle typedevices (e.g., automated cars that drive around a home). In some cases,the robotic devices 490 may be robotic devices 490 that are intended forother purposes and merely associated with the system 400 for use inappropriate circumstances. For instance, a robotic vacuum cleaner devicemay be associated with the monitoring system 400 as one of the roboticdevices 490 and may be controlled to take action responsive tomonitoring system events.

In some examples, the robotic devices 490 automatically navigate withina home. In these examples, the robotic devices 490 include sensors andcontrol processors that guide movement of the robotic devices 490 withinthe home. For instance, the robotic devices 490 may navigate within thehome using one or more cameras, one or more proximity sensors, one ormore gyroscopes, one or more accelerometers, one or more magnetometers,a global positioning system (GPS) unit, an altimeter, one or more sonaror laser sensors, and/or any other types of sensors that aid innavigation about a space. The robotic devices 490 may include controlprocessors that process output from the various sensors and control therobotic devices 490 to move along a path that reaches the desireddestination and avoids obstacles. In this regard, the control processorsdetect walls or other obstacles in the home and guide movement of therobotic devices 490 in a manner that avoids the walls and otherobstacles.

In addition, the robotic devices 490 may store data that describesattributes of the home. For instance, the robotic devices 490 may storea floorplan and/or a three-dimensional model of the home that enablesthe robotic devices 490 to navigate the home. During initialconfiguration, the robotic devices 490 may receive the data describingattributes of the home, determine a frame of reference to the data(e.g., a home or reference location in the home), and navigate the homebased on the frame of reference and the data describing attributes ofthe home. Further, initial configuration of the robotic devices 490 alsomay include learning of one or more navigation patterns in which a userprovides input to control the robotic devices 490 to perform a specificnavigation action (e.g., fly to an upstairs bedroom and spin aroundwhile capturing video and then return to a home charging base). In thisregard, the robotic devices 490 may learn and store the navigationpatterns such that the robotic devices 490 may automatically repeat thespecific navigation actions upon a later request.

In some examples, the robotic devices 490 may include data capture andrecording devices. In these examples, the robotic devices 490 mayinclude one or more cameras, one or more motion sensors, one or moremicrophones, one or more biometric data collection tools, one or moretemperature sensors, one or more humidity sensors, one or more air flowsensors, and/or any other types of sensor that may be useful incapturing monitoring data related to the home and users in the home. Theone or more biometric data collection tools may be configured to collectbiometric samples of a person in the home with or without contact of theperson. For instance, the biometric data collection tools may include afingerprint scanner, a hair sample collection tool, a skin cellcollection tool, and/or any other tool that allows the robotic devices490 to take and store a biometric sample that can be used to identifythe person (e.g., a biometric sample with DNA that can be used for DNAtesting).

In some implementations, the robotic devices 490 may include outputdevices. In these implementations, the robotic devices 490 may includeone or more displays, one or more speakers, and/or any type of outputdevices that allow the robotic devices 490 to communicate information toa nearby user.

The robotic devices 490 also may include a communication module thatenables the robotic devices 490 to communicate with the control unit410, each other, and/or other devices. The communication module may be awireless communication module that allows the robotic devices 490 tocommunicate wirelessly. For instance, the communication module may be aWi-Fi module that enables the robotic devices 490 to communicate over alocal wireless network at the home. The communication module further maybe a 900 MHz wireless communication module that enables the roboticdevices 490 to communicate directly with the control unit 410. Othertypes of short-range wireless communication protocols, such asBluetooth, Bluetooth LE, Z-wave, ZigBee, etc., may be used to allow therobotic devices 490 to communicate with other devices in the home. Insome implementations, the robotic devices 490 may communicate with eachother or with other devices of the system 400 through the network 405.

The robotic devices 490 further may include processor and storagecapabilities. The robotic devices 490 may include any suitableprocessing devices that enable the robotic devices 490 to operateapplications and perform the actions described throughout thisdisclosure. In addition, the robotic devices 490 may include solid-stateelectronic storage that enables the robotic devices 490 to storeapplications, configuration data, collected sensor data, and/or anyother type of information available to the robotic devices 490.

The robotic devices 490 are associated with one or more chargingstations. The charging stations may be located at predefined home baseor reference locations in the home. The robotic devices 490 may beconfigured to navigate to the charging stations after completion oftasks needed to be performed for the home monitoring system 400. Forinstance, after completion of a monitoring operation or upon instructionby the control unit 410, the robotic devices 490 may be configured toautomatically fly to and land on one of the charging stations. In thisregard, the robotic devices 490 may automatically maintain a fullycharged battery in a state in which the robotic devices 490 are readyfor use by the home monitoring system 400.

The charging stations may be contact based charging stations and/orwireless charging stations. For contact based charging stations, therobotic devices 490 may have readily accessible points of contact thatthe robotic devices 490 are capable of positioning and mating with acorresponding contact on the charging station. For instance, ahelicopter type robotic device may have an electronic contact on aportion of its landing gear that rests on and mates with an electronicpad of a charging station when the helicopter type robotic device landson the charging station. The electronic contact on the robotic devicemay include a cover that opens to expose the electronic contact when therobotic device is charging and closes to cover and insulate theelectronic contact when the robotic device is in operation.

For wireless charging stations, the robotic devices 490 may chargethrough a wireless exchange of power. In these cases, the roboticdevices 490 need only locate themselves closely enough to the wirelesscharging stations for the wireless exchange of power to occur. In thisregard, the positioning needed to land at a predefined home base orreference location in the home may be less precise than with a contactbased charging station. Based on the robotic devices 490 landing at awireless charging station, the wireless charging station outputs awireless signal that the robotic devices 490 receive and convert to apower signal that charges a battery maintained on the robotic devices490.

In some implementations, each of the robotic devices 490 has acorresponding and assigned charging station such that the number ofrobotic devices 490 equals the number of charging stations. In theseimplementations, the robotic devices 490 always navigate to the specificcharging station assigned to that robotic device. For instance, a firstrobotic device may always use a first charging station and a secondrobotic device may always use a second charging station.

In some examples, the robotic devices 490 may share charging stations.For instance, the robotic devices 490 may use one or more communitycharging stations that are capable of charging multiple robotic devices490. The community charging station may be configured to charge multiplerobotic devices 490 in parallel. The community charging station may beconfigured to charge multiple robotic devices 490 in serial such thatthe multiple robotic devices 490 take turns charging and, when fullycharged, return to a predefined home base or reference location in thehome that is not associated with a charger. The number of communitycharging stations may be less than the number of robotic devices 490.

Also, the charging stations may not be assigned to specific roboticdevices 490 and may be capable of charging any of the robotic devices490. In this regard, the robotic devices 490 may use any suitable,unoccupied charging station when not in use. For instance, when one ofthe robotic devices 490 has completed an operation or is in need ofbattery charge, the control unit 410 references a stored table of theoccupancy status of each charging station and instructs the roboticdevice to navigate to the nearest charging station that is unoccupied.

The system 400 further includes one or more integrated security devices480. The one or more integrated security devices may include any type ofdevice used to provide alerts based on received sensor data. Forinstance, the one or more control units 410 may provide one or morealerts to the one or more integrated security input/output devices 480.Additionally, the one or more control units 410 may receive sensor datafrom the sensors 420 and determine whether to provide an alert to theone or more integrated security input/output devices 480.

The sensors 420, the home automation controls 422, the camera 430, thethermostat 434, and the integrated security devices 480 may communicatewith the controller 412 over communication links 424, 426, 428, 432,438, and 484. The communication links 424, 426, 428, 432, 438, and 484may be a wired or wireless data pathway configured to transmit signalsfrom the sensors 420, the home automation controls 422, the camera 430,the thermostat 434, and the integrated security devices 480 to thecontroller 412. The sensors 420, the home automation controls 422, thecamera 430, the thermostat 434, and the integrated security devices 480may continuously transmit sensed values to the controller 412,periodically transmit sensed values to the controller 412, or transmitsensed values to the controller 412 in response to a change in a sensedvalue.

The communication links 424, 426, 428, 432, 438, and 484 may include alocal network. The sensors 420, the home automation controls 422, thecamera 430, the thermostat 434, and the integrated security devices 480,and the controller 412 may exchange data and commands over the localnetwork. The local network may include 802.11 “Wi-Fi” wireless Ethernet(e.g., using low-power Wi-Fi chipsets), Z-Wave, ZigBee, Bluetooth,“HomePlug” or other “Powerline” networks that operate over AC wiring,and a Category 5 (CATS) or Category 6 (CAT6) wired Ethernet network. Thelocal network may be a mesh network constructed based on the devicesconnected to the mesh network.

The monitoring server 460 is an electronic device configured to providemonitoring services by exchanging electronic communications with thecontrol unit 410, the one or more user devices 440 and 450, and thecentral alarm station server 470 over the network 405. For example, themonitoring server 460 may be configured to monitor events (e.g., alarmevents) generated by the control unit 410. In this example, themonitoring server 460 may exchange electronic communications with thenetwork module 414 included in the control unit 410 to receiveinformation regarding events (e.g., alerts) detected by the control unit410. The monitoring server 460 also may receive information regardingevents (e.g., alerts) from the one or more user devices 440 and 450.

In some examples, the monitoring server 460 may route alert datareceived from the network module 414 or the one or more user devices 440and 450 to the central alarm station server 470. For example, themonitoring server 460 may transmit the alert data to the central alarmstation server 470 over the network 405.

The monitoring server 460 may store sensor and image data received fromthe monitoring system 400 and perform analysis of sensor and image datareceived from the monitoring system 400. Based on the analysis, themonitoring server 460 may communicate with and control aspects of thecontrol unit 410 or the one or more user devices 440 and 450.

The monitoring server 460 may provide various monitoring services to thesystem 400. For example, the monitoring server 460 may analyze thesensor, image, and other data to determine an activity pattern of aresident of the home monitored by the system 400. In someimplementations, the monitoring server 460 may analyze the data foralarm conditions or may determine and perform actions at the home byissuing commands to one or more of the controls 422, possibly throughthe control unit 410.

The central alarm station server 470 is an electronic device configuredto provide alarm monitoring service by exchanging communications withthe control unit 410, the one or more mobile devices 440 and 450, andthe monitoring server 460 over the network 405. For example, the centralalarm station server 470 may be configured to monitor alerting eventsgenerated by the control unit 410. In this example, the central alarmstation server 470 may exchange communications with the network module414 included in the control unit 410 to receive information regardingalerting events detected by the control unit 410. The central alarmstation server 470 also may receive information regarding alertingevents from the one or more mobile devices 440 and 450 and/or themonitoring server 460.

The central alarm station server 470 is connected to multiple terminals472 and 474. The terminals 472 and 474 may be used by operators toprocess alerting events. For example, the central alarm station server470 may route alerting data to the terminals 472 and 474 to enable anoperator to process the alerting data. The terminals 472 and 474 mayinclude general-purpose computers (e.g., desktop personal computers,workstations, or laptop computers) that are configured to receivealerting data from a server in the central alarm station server 470 andrender a display of information based on the alerting data. Forinstance, the controller 412 may control the network module 414 totransmit, to the central alarm station server 470, alerting dataindicating that a sensor 420 detected motion from a motion sensor viathe sensors 420. The central alarm station server 470 may receive thealerting data and route the alerting data to the terminal 472 forprocessing by an operator associated with the terminal 472. The terminal472 may render a display to the operator that includes informationassociated with the alerting event (e.g., the lock sensor data, themotion sensor data, the contact sensor data, etc.) and the operator mayhandle the alerting event based on the displayed information.

In some implementations, the terminals 472 and 474 may be mobile devicesor devices designed for a specific function. Although FIG. 4 illustratestwo terminals for brevity, actual implementations may include more (and,perhaps, many more) terminals.

The one or more authorized user devices 440 and 450 are devices thathost and display user interfaces. For instance, the user device 440 is amobile device that hosts or runs one or more native applications (e.g.,the smart home application 442). The user device 440 may be a cellularphone or a non-cellular locally networked device with a display. Theuser device 440 may include a cell phone, a smart phone, a tablet PC, apersonal digital assistant (“PDA”), or any other portable deviceconfigured to communicate over a network and display information. Forexample, implementations may also include Blackberry-type devices (e.g.,as provided by Research in Motion), electronic organizers, iPhone-typedevices (e.g., as provided by Apple), iPod devices (e.g., as provided byApple) or other portable music players, other communication devices, andhandheld or portable electronic devices for gaming, communications,and/or data organization. The user device 440 may perform functionsunrelated to the monitoring system, such as placing personal telephonecalls, playing music, playing video, displaying pictures, browsing theInternet, maintaining an electronic calendar, etc.

The user device 440 includes a smart home application 442. The smarthome application 442 refers to a software/firmware program running onthe corresponding mobile device that enables the user interface andfeatures described throughout. The user device 440 may load or installthe smart home application 442 based on data received over a network ordata received from local media. The smart home application 442 runs onmobile devices platforms, such as iPhone, iPod touch, Blackberry, GoogleAndroid, Windows Mobile, etc. The smart home application 442 enables theuser device 440 to receive and process image and sensor data from themonitoring system.

The user device 450 may be a general-purpose computer (e.g., a desktoppersonal computer, a workstation, or a laptop computer) that isconfigured to communicate with the monitoring server 460 and/or thecontrol unit 410 over the network 405. The user device 450 may beconfigured to display a smart home user interface 452 that is generatedby the user device 450 or generated by the monitoring server 460. Forexample, the user device 450 may be configured to display a userinterface (e.g., a web page) provided by the monitoring server 460 thatenables a user to perceive images captured by the camera 430 and/orreports related to the monitoring system. Although FIG. 4 illustratestwo user devices for brevity, actual implementations may include more(and, perhaps, many more) or fewer user devices.

In some implementations, the one or more user devices 440 and 450communicate with and receive monitoring system data from the controlunit 410 using the communication link 438. For instance, the one or moreuser devices 440 and 450 may communicate with the control unit 410 usingvarious local wireless protocols such as Wi-Fi, Bluetooth, Z-wave,ZigBee, HomePlug (Ethernet over power line), or wired protocols such asEthernet and USB, to connect the one or more user devices 440 and 450 tolocal security and automation equipment. The one or more user devices440 and 450 may connect locally to the monitoring system and its sensorsand other devices. The local connection may improve the speed of statusand control communications because communicating through the network 405with a remote server (e.g., the monitoring server 460) may besignificantly slower.

Although the one or more user devices 440 and 450 are shown ascommunicating with the control unit 410, the one or more user devices440 and 450 may communicate directly with the sensors and other devicescontrolled by the control unit 410. In some implementations, the one ormore user devices 440 and 450 replace the control unit 410 and performthe functions of the control unit 410 for local monitoring and longrange/offsite communication.

In other implementations, the one or more user devices 440 and 450receive monitoring system data captured by the control unit 410 throughthe network 405. The one or more user devices 440, 450 may receive thedata from the control unit 410 through the network 405 or the monitoringserver 460 may relay data received from the control unit 410 to the oneor more user devices 440 and 450 through the network 405. In thisregard, the monitoring server 460 may facilitate communication betweenthe one or more user devices 440 and 450 and the monitoring system.

In some implementations, the one or more user devices 440 and 450 may beconfigured to switch whether the one or more user devices 440 and 450communicate with the control unit 410 directly (e.g., through link 438)or through the monitoring server 460 (e.g., through network 405) basedon a location of the one or more user devices 440 and 450. For instance,when the one or more user devices 440 and 450 are located close to thecontrol unit 410 and in range to communicate directly with the controlunit 410, the one or more user devices 440 and 450 use directcommunication. When the one or more user devices 440 and 450 are locatedfar from the control unit 410 and not in range to communicate directlywith the control unit 410, the one or more user devices 440 and 450 usecommunication through the monitoring server 460.

Although the one or more user devices 440 and 450 are shown as beingconnected to the network 405, in some implementations, the one or moreuser devices 440 and 450 are not connected to the network 405. In theseimplementations, the one or more user devices 440 and 450 communicatedirectly with one or more of the monitoring system components and nonetwork (e.g., Internet) connection or reliance on remote servers isneeded.

In some implementations, the one or more user devices 440 and 450 areused in conjunction with only local sensors and/or local devices in ahouse. In these implementations, the system 400 includes the one or moreuser devices 440 and 450, the sensors 420, the home automation controls422, the camera 430, the robotic devices 490, and the security system457. The one or more user devices 440 and 450 receive data directly fromthe sensors 420, the home automation controls 422, the camera 430, therobotic devices 490, and the security system 457 and sends data directlyto the sensors 420, the home automation controls 422, the camera 430,the robotic devices 490, and the security system 457. The one or moreuser devices 440, 450 provide the appropriate interfaces/processing toprovide visual surveillance and reporting.

In other implementations, the system 400 further includes network 405and the sensors 420, the home automation controls 422, the camera 430,the thermostat 434, the robotic devices 490, and the security system 457are configured to communicate sensor and image data to the one or moreuser devices 440 and 450 over network 405 (e.g., the Internet, cellularnetwork, etc.). In yet another implementation, the sensors 420, the homeautomation controls 422, the camera 430, the thermostat 434, the roboticdevices 490, and the security system 457 (or a component, such as abridge/router) are intelligent enough to change the communicationpathway from a direct local pathway when the one or more user devices440 and 450 are in close physical proximity to the sensors 420, the homeautomation controls 422, the camera 430, the thermostat 434, the roboticdevices 490, and the security system 457 to a pathway over network 405when the one or more user devices 440 and 450 are farther from thesensors 420, the home automation controls 422, the camera 430, thethermostat 434, the robotic devices 490, and the security system 457. Insome examples, the system leverages GPS information from the one or moreuser devices 440 and 450 to determine whether the one or more userdevices 440 and 450 are close enough to the sensors 420, the homeautomation controls 422, the camera 430, the thermostat 434, the roboticdevices 490, and the security system 457 to use the direct local pathwayor whether the one or more user devices 440 and 450 are far enough fromthe sensors 420, the home automation controls 422, the camera 430, thethermostat 434, the robotic devices 490, and the security system 457that the pathway over network 405 is required. In other examples, thesystem leverages status communications (e.g., pinging) between the oneor more user devices 440 and 450 and the sensors 420, the homeautomation controls 422, the camera 430, the thermostat 434, the roboticdevices 490, and the security system 457 to determine whethercommunication using the direct local pathway is possible. Ifcommunication using the direct local pathway is possible, the one ormore user devices 440 and 450 communicate with the sensors 420, the homeautomation controls 422, the camera 430, the thermostat 434, the roboticdevices 490, and the security system 457 using the direct local pathway.If communication using the direct local pathway is not possible, the oneor more user devices 440 and 450 communicate with the sensors 420, thehome automation controls 422, the camera 430, the thermostat 434, therobotic devices 490, and the security system 457 using the pathway overnetwork 405.

In some implementations, the system 400 provides end users with accessto images captured by the camera 430 to aid in decision-making. Thesystem 400 may transmit the images captured by the camera 430 over awireless WAN network to the user devices 440 and 450. Becausetransmission over a wireless WAN network may be relatively expensive,the system 400 can use several techniques to reduce costs whileproviding access to significant levels of useful visual information(e.g., compressing data, down-sampling data, sending data only overinexpensive LAN connections, or other techniques).

In some implementations, a state of the monitoring system 400 and otherevents sensed by the monitoring system 400 may be used to enable/disablevideo/image recording devices (e.g., the camera 430). In theseimplementations, the camera 430 may be set to capture images on aperiodic basis when the alarm system is armed in an “away” state, butset not to capture images when the alarm system is armed in a “home”state or disarmed. In addition, the camera 430 may be triggered to begincapturing images when the alarm system detects an event, such as analarm event, a door-opening event for a door that leads to an areawithin a field of view of the camera 430, or motion in the area withinthe field of view of the camera 430. In other implementations, thecamera 430 may capture images continuously, but the captured images maybe stored or transmitted over a network when needed.

The described systems, methods, and techniques may be implemented indigital electronic circuitry, computer hardware, firmware, software, orin combinations of these elements. Apparatus implementing thesetechniques may include appropriate input and output devices, a computerprocessor, and a computer program product tangibly embodied in amachine-readable storage device for execution by a programmableprocessor. A process implementing these techniques may be performed by aprogrammable processor executing a program of instructions to performdesired functions by operating on input data and generating appropriateoutput. The techniques may be implemented in one or more computerprograms that are executable on a programmable system including at leastone programmable processor coupled to receive data and instructionsfrom, and to transmit data and instructions to, a data storage system,at least one input device, and at least one output device. Each computerprogram may be implemented in a high-level procedural or object-orientedprogramming language, or in assembly or machine language if desired; andin any case, the language may be a compiled or interpreted language.Suitable processors include, by way of example, both general and specialpurpose microprocessors. Generally, a processor will receiveinstructions and data from a read-only memory and/or a random accessmemory. Storage devices suitable for tangibly embodying computer programinstructions and data include all forms of non-volatile memory,including by way of example semiconductor memory devices, such asErasable Programmable Read-Only Memory (EPROM), Electrically ErasableProgrammable Read-Only Memory (EEPROM), and flash memory devices;magnetic disks such as internal hard disks and removable disks;magneto-optical disks; and Compact Disc Read-Only Memory (CD-ROM). Anyof the foregoing may be supplemented by, or incorporated in, speciallydesigned ASICs (application-specific integrated circuits).

It will be understood that various modifications may be made. Forexample, other useful implementations could be achieved if steps of thedisclosed techniques were performed in a different order and/or ifcomponents in the disclosed systems were combined in a different mannerand/or replaced or supplemented by other components. Accordingly, otherimplementations are within the scope of the disclosure.

1. A computer-implemented method comprising: detecting, by a securitysystem for a premises, that a person who was within a threshold area forthe premises was likely uttering a sound; determining, using data fromone or more sensors, a likelihood that the person was communicating withthe security system at the premises; determining whether the likelihoodsatisfies a threshold likelihood and that the person's voice should notbe obfuscated; and in response to determining that the likelihood doesnot satisfy the threshold likelihood and that the person's voice shouldbe obfuscated, obfuscating the person's voice.
 2. The method of claim 1,wherein detecting that the person who was within the threshold area forthe premises was likely uttering a sound comprises detecting, usingvideo data captured by a camera, an image that depicts the person's lipsmoving.
 3. The method of claim 1, comprising retrieving, from a databasefor the premises, an audio signal encoding captured when the person waswithin the threshold area for the premises, wherein detecting that theperson was likely uttering a sound comprises detecting that the audiosignal likely encodes the voice of the person who was within thethreshold area for the premises.
 4. The method of claim 1, whereindetecting that the person who was within the threshold area for thepremises was likely uttering a sound comprises detecting, using audiodata captured by a microphone, an encoding of the person's voice.
 5. Themethod of claim 4, wherein determining the likelihood that the personwas communicating with the security system at the premises comprisesdetermining, using the audio data captured by the microphone, thelikelihood that the person was communicating with the security system atthe premises.
 6. The method of claim 5, wherein: determining thelikelihood that the person was communicating with the security system atthe premises comprises determining, using voice recognition, whether afirst signature for the person's voice matches a second signatureincluded in a database that includes one or more signatures, eachsignature of which is for a second person for which there is at least asecond threshold likelihood that the second person will be within asecond threshold area for the premises; and determining whether thelikelihood satisfies the threshold likelihood comprises determining thatthe likelihood does not satisfy the threshold likelihood and that theperson's voice should be obfuscated when the first signature matches thesecond signature.
 7. The method of claim 5, wherein: determining thelikelihood that the person was communicating with the security system atthe premises comprises determining, using voice recognition, whether afirst signature for the person's voice matches a second signatureincluded in a database that includes one or more anonymized signatures,each signature of which is for a second person for which there is atleast a second threshold likelihood that the second person will bewithin a second threshold area for the premises; and determining whetherthe likelihood satisfies the threshold likelihood comprises determiningthat the likelihood does not satisfy the threshold likelihood and thatthe person's voice should be obfuscated when the first signature matchesthe second signature.
 8. The method of claim 1, wherein obfuscating theperson's voice comprises removing, from an audio signal captured by amicrophone, an encoding of the person's voice.
 9. The method of claim 8,comprising maintaining, in the audio signal, an encoding of backgroundnoise that is separate from the encoding of the person's voice.
 10. Themethod of claim 1, wherein obfuscating the person's voice comprisesdetermining to skip initiating a recording of the person's voice by amicrophone.
 11. The method of claim 1, wherein determining thelikelihood that the person was communicating with the security system atthe premises uses the data from the one or more sensors physicallylocated at the premises.
 12. The method of claim 1, wherein determining,using the data from the one or more sensors, the likelihood that theperson was communicating with the security system at the premisescomprises determining one or more of: the likelihood that the person wasspeaking with a resident of the premises; the likelihood that the personspoke within a threshold time of a predetermined environmental sounddetected by the security system; or the likelihood that the person is anintruder at the premises who likely uttered the sound.
 13. A systemcomprising one or more computers and one or more storage devices onwhich are stored instructions that are operable, when executed by theone or more computers, to cause the one or more computers to performoperations comprising: detecting, by a security system for a premises,that a person who was within a threshold area for the premises waslikely uttering a sound; determining, using data from one or moresensors, a likelihood that the person was communicating with thesecurity system at the premises; determining whether the likelihoodsatisfies a threshold likelihood and that the person's voice should notbe obfuscated; and in response to determining that the likelihoodsatisfies the threshold likelihood and that the person's voice shouldnot be obfuscated, maintaining, in memory, an audio signal i) thatencodes the person's voice and ii) was captured by a microphone that wasphysically located at the premises.
 14. The system of claim 13, theoperations comprising: detecting that the person who was within thethreshold area for the premises was likely uttering a second sound;determining, using second data from the one or more sensors, a secondlikelihood that the person was communicating with the security system atthe premises by way of the second sound; determining whether the secondlikelihood satisfies the threshold likelihood and that the person'svoice for the second sound should not be obfuscated; and in response todetermining that the second likelihood does not satisfy the thresholdlikelihood and that the person's voice for the second sound should beobfuscated, obfuscating the person's voice for the second sound.
 15. Thesystem of claim 13, wherein detecting that the person who was within thethreshold area for the premises was likely uttering a sound comprisesdetecting, using video data captured by a camera, an image that depictsthe person's lips moving.
 16. The system of claim 13, the operationscomprising retrieving, from a database for the premises, an audio signalencoding captured when the person was within the threshold area for thepremises, wherein detecting that the person was likely uttering a soundcomprises detecting that the audio signal likely encodes the voice ofthe person who was within the threshold area for the premises.
 17. Thesystem of claim 13, wherein: determining the likelihood that the personwas communicating with the security system at the premises comprisesdetermining, using voice recognition, whether a first signature for theperson's voice matches a second signature included in a database thatincludes one or more signatures, each signature of which is for a secondperson for which there is at least a second threshold likelihood thatthe second person will be within a second threshold area for thepremises; and determining whether the likelihood satisfies the thresholdlikelihood comprises determining that the likelihood satisfies thethreshold likelihood and that the person's voice should not beobfuscated when the first signature does not match the second signature.18. The system of claim 13, wherein: determining the likelihood that theperson was communicating with the security system at the premisescomprises determining, using voice recognition, whether a firstsignature for the person's voice matches a second signature included ina database that includes one or more anonymized signatures, eachsignature of which is for a second person for which there is at least asecond threshold likelihood that the second person will be within asecond threshold area for the premises; and determining whether thelikelihood satisfies the threshold likelihood comprises determining thatthe likelihood satisfies the threshold likelihood and that the person'svoice should not be obfuscated when the first signature does not matchthe second signature.
 19. One or more non-transitory computer storagemedia encoded with instructions that, when executed by one or morecomputers, cause the one or more computers to perform operationscomprising: detecting, by a security system for a premises, that aperson who was within a threshold area for the premises was likelyuttering a sound; determining, using data from one or more sensors, alikelihood that the person was communicating with the security system atthe premises; determining whether the likelihood satisfies a thresholdlikelihood and that the person's voice should not be obfuscated; and inresponse to determining that the likelihood does not satisfy thethreshold likelihood and that the person's voice should be obfuscated,obfuscating the person's voice.
 20. The computer storage media of claim19, wherein detecting that the person who was within the threshold areafor the premises was likely uttering a sound comprises detecting, usingvideo data captured by a camera, an image that depicts the person's lipsmoving.